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. 2011 Mar 17;7(3):e1002013. doi: 10.1371/journal.pcbi.1002013

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Lüling et al.

This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.

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(A) Test error as a function of the number of classifications bins for five different numbers of training samples ( as indicated by grey level). Training errors are plotted as solid lines, test errors (localization acuity) are plotted as dashed lines. (B) Difference in test errors (black) and single-cell mutual information (grey) as a function of the rotation angle. Positive differences indicate that the value obtained with the non-rotated CP-CD distribution is larger. For the linear classifiers, the number of training samples was . (C) Test error as a function of the number of input neurons for the actually measured CP-CD distribution (solid line), for the optimal rotation angle (dashed line), and for CP set to zero (grey). (D) Optimal rotation angles at which the test error difference from B has local maximum.

Inline graphic — (A) Test error as a function of the number of classifications bins for five different numbers of training samples ( as indicated by grey level). Training errors are plotted as solid lines, test errors (localization acuity) are plotted as dashed lines. (B) Difference in test errors (black) and single-cell mutual information (grey) as a function of the rotation angle. Positive differences indicate that the value obtained with the non-rotated CP-CD distribution is larger. For the linear classifiers, the number of training samples was . (C) Test error as a function of the number of input neurons for the actually measured CP-CD distribution (solid line), for the optimal rotation angle (dashed line), and for CP set to zero (grey). (D) Optimal rotation angles at which the test error difference from B has local maximum.